Predictive Models in
Software Engineering

This international conference seeks repeatable methods for building verifiable models, useful for implementation, evaluation, & management of software development
projects
(both in general or for specific domains like telecom, finance, scientific applications, etc).

Tools for software researchers that effectively gather and analyze data to support reproducible and verifiable research.

THEME: The theme of PROMISE’12 is the next generation of empirical SE (next-gen). While we encourage submission of the traditional style of PROMISE papers, we also seek “next gen” papers that extend this area in significant new directions (see notes below)

KEYNOTE SPEAKERS:Martin Shepperd: "The scientific basis for prediction research":
In recent years there has been a huge growth in using statistical and machine learning methods to find useful prediction systems for software engineers. Of particular interest is predicting project effort and duration and defect behaviour. Unfortunately though results are often promising no single technique dominates and there are clearly complex interactions between technique, training methods and the problem domain. Since we lack deep theory our research is of necessity experimental. Minimally, as scientists, we need reproducible studies. We also need comparable studies. I will show through a meta-analysis of many primary studies that we are not presently in that situation and so the scientific basis for our collective research remains in doubt. By way of remedy I will argue that we need to address issues of expertise, reporting protocols and ensure blind analysis is routine.

Sung Kim: "Defect, Defect, Defect: Defect Prediction 2.0":
Software prediction leveraging repositories has received a tremendous amount of attention within the software engineering community, including PROMISE. In this talk, I will first present great achievements in defect prediction research including new defect prediction features, promising algorithms, and interesting analysis results. However, there are still many challenges in defect prediction. I will talk about them and discuss potential solutions for them leveraging prediction 2.0.

Data

PROMISE 2012 will give the highest priority to empirical studies based on publicly available datasets. It is therefore encouraged, but it is not mandatory, that conference attendees contribute the data used in their analysis to the on-line PROMISE data repository. The repository currently holds 142 data sets, which can be used to repeat/confirm/refute/improve previous results.

Important Dates

Abstracts due: March 26, 2012

Paper submission: April 2 April 16, 2012

Notification: May 14, June 11, 2012

Camera-ready papers : June 11, July 9, 2012

Kinds of Papers

This conference encourages both standard papers and next-gen papers (and note that only
next-gen papers can be submitted for consideration to the special journal issue associated with this conference).

Next-gen papers focus
on all the issues that surround predictive models. For discussions on next generation predictive modeling see
(a) the ICSE’11 tutorial on Empirical SE, version 2.0 at
http://goo.gl/MWzlq;
or
(b)
the “Special Issue Notes” at
http://goo.gl/b3E05.
Issues relevant to next-gen papers include, but are not restricted to the following:

Before a predictive model is built:

Privacy concerns of the individual and the corporate must be addressed.

Special Issue

Papers accepted to PROMISE’12 may also be submitted to a forthcoming special journal issue on “Empirical Software Engineering, version 2.0”.

Authors with good reviews from PROMISE’12 are strongly encouraged to submit to this special issue since several reviewers used for PROMISE’12 will also review papers for this issue.

It is a requirement for all submissions to the special issue to have some section called “Empirical SE, V2.0” that discusses next gen issues; i.e. how their work fits into the broader picture beyind just building a predictor (see notes, above).

Venue for Special Issue

The venue for that special issue is TBD.

Previous PROMISE special issues have appeared in IEEE Software, the Empirical Software Engineering journal, and the information and Software Technology Journal.